35 related articles

A systematic guide to AI Agent development covering the three-stage learning path, core tech stack including LLM, RAG, and LangChain, plus how to build a one-person company through automated Agent workflows.
Learning AI Agent Development from Scr…
A comprehensive guide to AI Agent development for beginners, covering low-code platforms, LangChain framework, and monetization strategies for building and deploying intelligent agents.
AI Agent Global Variable Pool & Memory…
Deep dive into global variable pool design for AI Agent development, covering three memory types, variable scoping, node execution architecture, and placeholder variable replacement workflows.

Deep dive into LlamaFactory, an open-source unified fine-tuning framework supporting 100+ LLMs and VLMs with LoRA, QLoRA, RLHF methods, Web UI, 71K+ GitHub Stars, accepted at ACL 2024.

Deep dive into vLLM's core technologies for high-throughput LLM inference, including PagedAttention memory management, continuous batching, distributed deployment, and comparisons with TensorRT-LLM.

AI bot replies have forced social media users to restrict interactions. Worse, bots now use Quote Tweets to bypass defenses. Analysis of AI pollution evolution and platform governance challenges.

Deep dive into Firebase AI Logic's two major security updates: Template-only mode locks server-side prompts to prevent injection, and Authentication mode enforces identity verification to prevent API abuse.

Deep dive into OpenAI Swarm multi-agent orchestration framework, explaining Function Call tool invocation and Handoff task transfer mechanisms with local deployment guide.
TutorialsRAG (Retrieval-Augmented Generation) is the core solution for LLM hallucination. Learn RAG concepts, how it works, three causes of hallucination, and the complete learning path from basics to Knowledge Graph RAG.
TutorialsA detailed guide to Ollama's core features: free open-source local LLM management with cross-platform support, intelligent GPU/CPU scheduling, and API integration for running DeepSeek and other open-source models locally at zero cost.
TutorialsLearn how to deploy LLMs locally with Ollama in three simple steps: install, choose a model, and run. No coding required, supports offline use, and completely free.
Deep DivesDeep dive into how MCP (Model Context Protocol) solves three core pain points of Tool Calling: verbose descriptions, unstable invocations, and lack of unified standards.
TutorialsIn-depth analysis of Google's Gemma 4 open-source models: 31B, 26B MOE, and 14B/12B benchmarks, deployment guides for all platforms, and MS-Swift fine-tuning tutorial for building local Agent workflows.
TutorialsLearn how to use AI agents to auto-generate Excel test cases. Covers Coze platform setup, Dify private deployment with DeepSeek + Ollama, workflow design tips, and prompt engineering for testers.
TutorialsStep-by-step tutorial on deploying Dify locally using VMware, Ubuntu, BT Panel, and Docker. Covers environment setup, common error fixes, and next steps for building AI apps.
TutorialsDeep dive into Claude Code's four core agent modules: system prompt, Agent Loop, tool system, and memory mechanism. Build a Mini Claude Code from scratch in TypeScript.
TutorialsA systematic guide to LLM engineer core skills covering RAG, Agent app development and SFT, RLHF fine-tuning, with clear learning paths for different backgrounds.
TutorialsDeep analysis of Claude Code's four core agent modules: Agent Loop, Tool System, Skills, and Memory, with a TypeScript minimal implementation guide for frontend engineers transitioning to AI development.
TutorialsComplete guide to connecting Codex with DeepSeek V4 via CC Switch relay, including API Key setup, channel configuration, and plugin unlock steps for cost-effective AI programming.
TutorialsDeep analysis of interview trends for Java developers transitioning to AI engineers, covering LLM integration, RAG, Spring AI framework practice, with a complete learning roadmap.